Sizing ice hydrometeor populations using dual-wavelength radar ratio Journal Article uri icon

Overview

abstract

  • Abstract. Dual-wavelength (3.2 and 0.32 cm, i.e., X- and W- radar bands) radar ratio (DWR) measurements in ice clouds and precipitation using the Canada’s National Research Council Institute for Aerospace Research airborne radar are compared to closely collocated particle microphysical in situ sampling data in order to develop relations between DWR and characteristic hydrometeor size. This study uses the radar and in situ data sets collected during the In-Cloud ICing and Large-drop Experiment (ICICLE) campaign. Since atmospheric particle scattering at X-band is predominately in the Rayleigh regime and the W-band frequency is the highest frequency usually used for hydrometeor remote sensing, the X-W-band combination provides relatively strong dual-wavelength reflectivity difference. This study considers radar and in situ measurements conducted in relatively homogeneous cloud and precipitation conditions. Measurements show that under these conditions, the difference between the X-band radar reflectivities observed with vertical and horizontal pointing of the radar beam are generally small and often negligible. However, W-band band reflectivities at vertical beam pointing are, on average, larger than those for horizontal beam pointing by about 4 dB, which is a non-Rayleigh scattering effect from oriented non-spherical particles. A horizontal beam DWR – mean volume particle size, Dv, relation provides robust estimates of this characteristic size for populations of particles with different habits. Uncertainties of Dv retrievals using DWR are around 0.6 mm when Dv is greater than approximately 1 mm. Size estimates using vertical radar beam DWRs have larger uncertainties due to smaller dual-wavelength signals and stronger influences of hydrometeor habits and orientations at this geometry of beam pointing. Mean relationships among different characteristic sizes describing the entire particle size distribution (PSD) such as Dv, and other characteristic sizes used in different applications (e.g., the mean, effective, and median sizes) are derived, so the results of this study can be used for estimating different PSD characteristic sizes.;

publication date

  • June 7, 2022

has restriction

  • green

Date in CU Experts

  • June 7, 2022 11:13 AM

Full Author List

  • Matrosov SY; Korolev A; Wolde M; Nguyen C

author count

  • 4

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